Crop constituent map generation and control system

Abstract

One or more maps are obtained by an agricultural work machine. The one or more maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

What is claimed is: 
     
       1. An agricultural work machine, comprising:
 a communication system that receives a map that includes values of an agricultural characteristic corresponding to different geographic locations in a field; 
 a geographic position sensor that detects a geographic location of the agricultural work machine; 
 an in-situ sensor that detects a value of a crop constituent corresponding to the geographic location; 
 a controllable subsystem; 
 one or more processors; 
 memory, wherein computer executable instructions are stored in the memory, the computer executable instructions, when executed by the one or more processors, configuring the one or more processors to:
 generate a predictive agricultural model that models a relationship between the agricultural characteristic and the crop constituent based on a value of the agricultural characteristic in the map at the geographic location and the value of the crop constituent detected by the in-situ sensor corresponding to the geographic location; 
 generate a functional predictive agricultural map of the field that maps predictive values of the crop constituent to the different geographic locations in the field, based on the values of the agricultural characteristic in the map and based on the predictive agricultural model; and 
 generate a control signal to control the controllable subsystem based on the functional predictive agricultural map. 
 
 
     
     
       2. The agricultural work machine of  claim 1 , wherein the control signal controls the controllable subsystem to control a speed of a cleaning fan on the agricultural work machine. 
     
     
       3. The agricultural work machine of  claim 1 , wherein the control signal controls the controllable subsystem to control a size of openings on a chaffer on the agricultural work machine. 
     
     
       4. The agricultural work machine of  claim 1 , wherein the map comprises a vegetative index map that includes, as the values of the agricultural characteristic, vegetative index values corresponding to the different geographic locations in the field. 
     
     
       5. The agricultural work machine of  claim 4 , wherein the computer executable instructions, when executed by the one or more processors, further configure the one or more processors to identify a relationship between crop constituent values and the vegetative index values based on the value of the crop constituent detected by the in-situ sensor corresponding to the geographic location and a vegetative index value, in the vegetative index map, at the geographic location, the predictive agricultural model being configured to receive a vegetative index value, in the vegetative index map, at a different geographic location, as a model input and generate a predictive value of the crop constituent, corresponding to the different geographic location, as a model output based on the identified relationship. 
     
     
       6. The agricultural work machine of  claim 1 , wherein the map comprises a historical crop constituent map that includes, as the values of the agricultural characteristic, historical values of the crop constituent corresponding to the different geographic locations in the field. 
     
     
       7. The agricultural work machine of  claim 6 , wherein the computer executable instructions, when executed by the one or more processors, further configure the one or more processors to identify a relationship between crop constituent values and the historical values of the crop constituent based on the value of the crop constituent detected by the in-situ sensor corresponding to the geographic location and a historical value of the crop constituent, in the historical crop constituent map, at the geographic location, the predictive agricultural model being configured to receive a historical value of the crop constituent, in the historical crop constituent map, at a different geographic location, as a model input and generate a predictive value of the crop constituent, corresponding to the different geographic location, as a model output based on the identified relationship. 
     
     
       8. The agricultural work machine of  claim 1 , wherein the map comprises a predictive map that maps, as the values of the agricultural characteristic, predictive values of the agricultural characteristic corresponding to the different geographic locations in the field. 
     
     
       9. The agricultural work machine of  claim 8 , wherein the computer executable instructions, when executed by the one or more processors, further configure the one or more processors to identify a relationship between crop constituent values and the predictive values of the agricultural characteristic, based on the value of the crop constituent detected by the in-situ sensor corresponding to the geographic location and a predictive value of the agricultural characteristic, in the predictive map, at the geographic location, the predictive agricultural model being configured to receive a predictive value of the agricultural characteristic value, in the predictive map, at a different geographic location, as a model input and generate a predictive value of the crop constituent, corresponding to the different geographic location, as a model output based on the identified relationship. 
     
     
       10. The agricultural work machine of  claim 1 , wherein the map comprises a soil property map that maps, as the values of the agricultural characteristic, values of a soil property corresponding to the different geographic locations in the field. 
     
     
       11. The agricultural work machine of  claim 10 , wherein the computer executable instructions, when executed by the one or more processors, further configure the one or more processors to identify a relationship between crop constituent values and values of the soil property based on the value of the crop constituent detected by the in-situ sensor corresponding to the geographic location and a value of the soil property, in the soil property map, at the geographic location, the predictive agricultural model being configured to receive a value of the soil property, in the soil property map, at a different geographic location, as a model input and generate a predictive value of the crop constituent, corresponding to the different geographic location, as a model output based on the identified relationship. 
     
     
       12. The agricultural work machine of  claim 1 , further comprising an additional in-situ sensor that detects a value of an additional agricultural characteristic corresponding to an additional geographic location, wherein the computer executable instructions, when executed by the one or more processors, further configure the one or more processors to:
 generate an additional agricultural model that models a relationship between the additional agricultural characteristic and the crop constituent based on the value of the additional agricultural characteristic detected by the additional in-situ sensor corresponding to the additional geographic location and a predictive value of the crop constituent in the functional predictive agricultural map at the additional geographic location; 
 generate an additional functional predictive agricultural map of the field that maps predictive values of the additional agricultural characteristic to the different geographic locations in the field, based on the predictive values of the crop constituent in the functional predictive agricultural map and based on the additional agricultural model; and 
 generate the control signal to control the controllable subsystem based on the additional functional predictive agricultural map. 
 
     
     
       13. A computer implemented method of controlling an agricultural work machine, the computer implement method comprising:
 receiving, at the agricultural work machine, a map that includes values of an agricultural characteristic corresponding to different geographic locations in a field; 
 detecting a geographic location of the agricultural work machine; 
 detecting, with an in-situ sensor, a value of a crop constituent corresponding to the geographic location; 
 generating a predictive agricultural model that models a relationship between the agricultural characteristic and the crop constituent; 
 generating a functional predictive agricultural map of the field that maps predictive values of the crop constituent to the different locations in the field based on the values of the agricultural characteristic in the map and the predictive agricultural model; and 
 generating a control signal to control a controllable subsystem of the agricultural work machine based on the functional predictive agricultural map. 
 
     
     
       14. The computer implemented method of  claim 13 , wherein generating the control signal comprises one of:
 generating the control signal to control the controllable subsystem to control a speed of a cleaning fan on the agricultural work machine; or 
 generating the control signal to control the controllable subsystem to control a size of openings on a chaffer on the agricultural work machine. 
 
     
     
       15. The computer implemented method of  claim 13 , wherein receiving the map comprises receiving a vegetative index map that includes, as the values of the agricultural characteristic, vegetative index values corresponding to the different geographic locations in the field. 
     
     
       16. The computer implemented method of  claim 15 , wherein generating the predictive agricultural model comprises:
 identifying a relationship between the vegetative index and the crop constituent based on the value of the crop constituent corresponding to the geographic location and a vegetative index value, in the vegetative index map, at the geographic location; and 
 generating the predictive agricultural model that receives a vegetative index value, in the vegetative index map, at a different geographic location, as a model input and generates a predictive value of the crop constituent, corresponding to the different geographic location, as a model output based on the identified relationship. 
 
     
     
       17. The computer implemented method of  claim 13 , wherein receiving the map comprises receiving a historical crop constituent map that includes, as the values of the agricultural characteristic, historical values of the crop constituent corresponding to the different geographic locations in the field. 
     
     
       18. The computer implemented method of  claim 17 , wherein generating the predictive agricultural model comprises:
 identifying a relationship between the historical crop constituent values and the crop constituent based on the value of the crop constituent corresponding to the geographic location and a historical value of the crop constituent, in the historical crop constituent map, at the geographic location; and 
 generating the predictive agricultural model that receives a historical value of the crop constituent, in the historical crop constituent map, at a different geographic location, as a model input and generates a predictive value of the crop constituent, corresponding to the different geographic location, as a model output based on the identified relationship. 
 
     
     
       19. The computer implemented method of  claim 13 , further comprising:
 controlling an operator interface mechanism to present the functional predictive agricultural map. 
 
     
     
       20. An agricultural system, comprising:
 a communication system that receives a map that indicates values of an agricultural characteristic corresponding to different geographic locations in a field; 
 a geographic position sensor that detects a geographic location of the agricultural work machine; 
 an in-situ sensor that detects a value of a crop constituent corresponding to the geographic location; 
 a controllable subsystem; 
 one or more processors; 
 memory, wherein computer executable instructions are stored in the memory, the computer executable instructions, when executed by the one or more processors, configuring the one or more processors to:
 generate a predictive crop constituent model that models a relationship between the agricultural characteristic and the crop constituent based on a value of the agricultural characteristic in the map at the geographic location and the value of the crop constituent detected by the in-situ sensor corresponding to the geographic location; 
 generate a functional predictive crop constituent map of the field, that maps predictive values of the crop constituent to the different locations in the field, based on the agricultural characteristic values in the map and based on the predictive crop constituent model; and 
 generate a control signal to control the controllable subsystem based on the functional predictive crop constituent map.